Data Scientist, Engineering Simulation (Hybrid in Cambridge, MA or Thousand Oaks, CA)

Data Scientist – Engineering Simulation Location: Hybrid – Cambridge, MA or Thousand Oaks, CA (3 days/week onsite; some weeks may vary) Contract: 12 months to start,with possible extension Pay Rate: $57/hr Join a leading biopharmaceutical company where innovation and science drive real-world impact. Work at the intersection of engineering and data analytics, solving complex problems that influence drug development. Enjoy a hybrid work environment, professional growth opportunities, and the chance to make a difference in global healthcare. About the Role: Amgen is seeking a Data Scientist with a strong engineering background (preferably Mechanical, Biomedical, or Chemical Engineering) to join our team. This role focuses on simulation, modeling, and data analysis in a GMP-regulated environment. The ideal candidate is highly analytical, collaborative, and able to translate experimental data into actionable insights that impact drug development and patient outcomes. Key Responsibilities: • Develop and implement engineering models for structural, fluidic, and heat transfer problems. • Perform simulation and analysis using commercial FEM solvers (ABAQUS, ANSYS, LS-Dyna, COMSOL). • Apply numerical techniques, uncertainty quantification, and Monte Carlo simulations to engineering problems. • Use Python, MATLAB, JMP, and/or Minitab for data analysis, modeling, and simulation tasks. • Collaborate with cross-functional teams to translate experimental results into actionable insights. • Participate in technical interviews and demonstrate applied engineering simulation experience. Education & Experience Requirements: • PhD: No industry experience required (must have simulation-focused thesis/research). • Master’s: At least 2 years of relevant industry experience. • Bachelor’s: Minimum 4 years of relevant experience. • Strictly software-only backgrounds (CS, CE, EE) are not eligible. • Must have biotech or medical device experience. Must-Have Skills: 1. Python, MATLAB, JMP, and/or Minitab for engineering purposes. 1. Experience with commercial FEM solvers (ABAQUS, ANSYS, LS-Dyna, COMSOL) for simulation and modeling. 1. Expertise in numerical techniques, mathematical/first-principles modeling, and uncertainty quantification (e.g., Monte Carlo simulations). Information Needed (to be included on top of resume if selected to move forward): 1. How do you determine if an internal flow is laminar or turbulent? 1. What is your experience with FEM commercial solvers, and which ones have you used? 1. Explain the difference between explicit and implicit FEM methods. 1. What is your experience with Python, and which libraries have you used for data analysis, modeling, or simulation? 1. Are you familiar with GitLab? Describe typical operations you’ve performed. 1. Are you familiar with Monte Carlo analysis? How do you ensure convergence in a Monte Carlo model? Interview Process: Phone screening → Panel interview Note: • Overqualified candidates (graduate degrees with 7–8+ years experience) may not align with the role. • Candidates with applied simulation experience in mechanical/biomedical engineering domain experience are the goal hires.